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Baseline haematological parameters in three common Australian frog species.

Tara Jadwani-BungarNicholas P DoidgeDanielle K WallaceLaura A Brannelly
Published in: PeerJ (2024)
Amphibians are experiencing declines globally, with emerging infectious diseases as one of the main causes. Haematological parameters present a useful method for determining the health status of animals and the effects of particular diseases, but the interpretation of differential cell counts relies on knowing the normal ranges for the species and factors that can affect these counts. However, there is very little data on either normal haematological parameters or guides for blood cell types for free-ranging frog species across the world. This study aims to 1) create a visual guide for three different Australian frog species: Litoria paraewingi , Limnodynastes dumerilii , and Crinia signifera , 2) determine the proportions of erythrocytes to leukocytes and 3) differential leukocytes within blood smears from these three species and 4) assess the association between parasites and differential counts. We collected blood samples from free-ranging frogs and analysed blood smears. We also looked for ectoparasites and tested for the fungal disease chytridiomycosis. Overall, we found that the differentials of erythrocytes to leukocytes were not affected by species, but the proportions of different leukocytes did vary across species. For example, while lymphocytes were the most common type of leukocyte across the three species, eosinophils were relatively common in Limnodynastes dumerilii but rarely present in the other two species. We noted chytridiomycosis infection as well as ectoparasites present in some individuals but found no effect of parasites on blood parameters. Our results add baseline haematological parameters for three Australian frog species and provide an example of how different frog species can vary in their differential blood cell counts. More information is needed on frog haematological data before these parameters can be used to determine the health status of wild or captive frogs.
Keyphrases
  • peripheral blood
  • genetic diversity
  • stem cells
  • healthcare
  • infectious diseases
  • machine learning
  • big data
  • mesenchymal stem cells
  • social media
  • deep learning
  • cell wall